The AI mystique might be the biggest obstacle to AI adoption. The artisanal data scientist who works on an alchemy of code output the magical algorithm impedes discussion on what is needed to commercialize and scale AI solutions. AI needs to be treated like a product and an item to be manufactured and scaled on an industrial level.
This article summarizes the main takeaways as discussed in the panel „What is the future of AI adoption?“ at Rework’s Enterprise AI Summit in Berlin.
The major challenges to AI implementation are often mind-set based rather than technical. Problems in production and implementation of AI often stem from organizations‘ and practitioners‘ lack of ability and/or desire to thoroughly scope out and define the problem they are trying to solve. Consequently, they often don’t select the right tools, capabilities and processes to implement successfully. Organizations can also negelct operations (such as MLOps), which are important for work efficacy and scale.